Clean Technology Meets Data Science: News and Articles

  Since our last post discussing the market demand for clean tech data scientists and the potentially high growth in the years ahead, we've been getting a lot of questions from our readers about jobs, careers, salaries and how to get hired. Since most of the answers are going to be longer than a single blog post, we've decided to host a webinar discussing Careers in Clean Technology and Data Science.  The webinar will be held on April 26th, so please register   here   to reserve your spot. And if you do miss it or can't make it, don't worry! We'll host another one later in the year and in the meantime, we'll have the slides from the presentation available for download.

  We’ll be doing a series of posts discussing careers at the intersection of data science and clean technology - what kind of jobs are there, what career paths do they lead to, where can you work and what are typical salaries in this field.   The market for clean technology and data science is still in its infancy, but growing rapidly.   The market is divided between several sectors (energy, agriculture, water, climate change) to name a few  and each of these sectors has a market size ranging from multi-million to several trillion dollars.   As data science, including the use of sensors, machine learning, imagery and statistics, penetrates each sector , the market for clean technology and data science becomes correspondingly large. In fact, it’s been   estimated that we could be looking at a market size   between   100   billion to 6 trillion dollars   worldwide by 2025 . To put that in perspective, the software industry in the US has a market size of close to $2 trillion dollars today

Last time   we looked at the kind of applications in clean technology where using virtual reality or augmented reality systems are making a significant difference.     But, how do these systems work?   Most AR and VR systems can be broadly classified as follows. These systems can be divided into 1) the hardware required to get the data, process and display it 2) the software needed to develop simulations of the systems being studied and create virtual objects and 3) the server where the data are stored and processed and where machine learning algorithms can be deployed to improve outcomes.   Key Hardware systems : The hardware systems can be categorized into the input systems and the display systems.     Most AR and VR systems use GPS (to determine location), cameras (to obtain the live images of where the user is located and/or looking), gyroscopes and accelerometers (to determine speed and direction of the user’s movement) and other sensors that are specific to the problem being solv

What do the terms Virtual Reality (VR) and Augmented Reality (AR) bring to mind? Hollywood movies like “Black Panther” with the crazy action sequences where cars and airplanes are controlled from a laboratory, games like World of Warcraft with your gaming character moving through all the different locations, Pokemon Go and hunting for the prize in an actual physical location, Star Trek holodecks where you could explore completely different planets and surfaces… the list goes on and on. The one thing that all these examples have in common though is that they all come from the entertainment industry.   Now, VR and AR have been used extensively in playing games, having fun, and making movies more realistic. However, as devices like Google Cardboard, Oculus Rift and HTC’s Vive become more widely available and affordable, VR and AR have begun making their way into fields beyond just entertainment. In clean tech, in particular, there’s been increased interest in ways in which these technolog

  My last post talked about how ideas get transferred from the laboratory to markets so that they can be used by millions of people. What I’m going to talk about today is the other side of the coin – the way millions of people can use smartphones and today’s tech to help advance scientific research and improve the world.   In other words –   citizen scientists   and how they help the clean tech and big data fields. One place where the community has been essential in understanding what’s going on in our world is in biodiversity and wildlife monitoring. Collecting data about where the different species are, what’s going on with their habitats has always been something that is hard and expensive to do for scientists. Imagine the effort it takes to distribute sensors and collect enough data about animals like tigers and bears!   Scientists and policy makers have always relied to some extent on data collected by enthusiastic amateurs to help round out their data collection efforts in these

  We hear a lot about the Elon Musks of the world – what makes them tick, how they see the future of clean technology and what they would do about it. But, what’s perhaps not very well known is how much of what gets built into these new products and new markets owes its start to government funding and policies. Today, I want to walk through the way innovative new technology moves from the research laboratory to the market via government. A fascinating study was published in   Nature Communications   about integrating “solar ribbons” into fabric so that in the future our clothes could harvest sunlight and store energy to power phones, health sensors or any other device. The scientists said that this research was inspired by the movie “Back to the Future” – but it needed a lot of cool technology to come together to actually make the prototype work. First – how can energy be harvested in a thin, flexible form? Enter the perovskite solar cell- a technology with several years of basic resea

  Perhaps one of the most interesting parts of trying to clean up the environment is the need to balance individual action with global behavior. Actions that are optimal at the individual level are often what lead to depletion of resources and environmental damage at the global or regional scale. Take climate change for example – even though the effects of a changing climate promise to be devastating to many countries and places around the world, it has often worked better for countries to focus on their short-term economic goals rather than look at what would work best for the economy and environment in the long term. A  recent approach  from scientists at Georgia Tech looks at how game theory can be used to help solve this problem. An assumption inherent in how many environmental policies and markets are designed is that actors will act rationally in their own interest and that the system doesn’t change drastically. Now, this is an assumption that doesn’t necessarily hold true in man

  It’s tempting sometimes to think that we can grab all the lovely data lying around, feed it into a computer algorithm and then get results that magically tell us something new and amazing. That though is the tired data scientist’s fantasy – and thinking about problems that way doesn’t really help solve them! We’re always going to need what’s now being called “domain expertise” in data science circles – that deep understanding of your subject and the expertise that lets you understand when data is valuable, what insights really are insights and when to use the data scientist’s vast array of tools.   A study that was published in   PLOS One   today is a perfect example of how a data scientist typically works through problems in the clean tech space – together with all the associated complications.   The question that was asked in this study was this – “Can I use data about how people commute to understand which regions are economically dominant – that is megaregions?”   So, starting of

  Several interesting research studies have been written highlighting how data science is being embedded in clean tech. What I find fascinating is that these stories showcase research at very different scales – at the micro level and at the scale of the Earth System. The first study that came out this week was by teams from the University of California, Irvine and NASA’s Jet Propulsion Laboratory evaluating the melting of Antarctica’s glaciers. The teams used satellite data to monitor the location and movement over the years of the glaciers “grounding line” – the point at which the glacier begins to float while still attached to the land. The reason that’s important is because it helps determine how much ice is melting into the oceans – with all the associated implications for understanding sea level rise in a changing climate. The recent data (2014-2016) came from the Sentinel-1 mission launched by the European Space Agency and the previous years data (1992,1996 and 2011) that was use

  How many times did you think about water this month? If you’re like most people in developed countries, you probably only thought about it when paying your water bill – or if there were news articles about floods or droughts or oceans. If you’re in parts of the world where water is not plentiful, the chances are that you thought about it if you had to plan your day around when water was going to come out of the tap. If, like many of the poor, you had to walk miles or stand in queues to collect drinking water, you probably spent a large part of your day thinking about it. Water is essential to life and yet, we don’t hear a great deal about innovation or venture capital funding or startups that are changing the world in this sector in popular media or news. Which brings up the question – where is the funding for innovation in this sector? Venture capital funding in water is a relatively small investment compared to the investment in high-tech or even in some of the other clean tech sec

  “Supply and demand” is a phrase that’s more commonly associated with economics and business than with the environment. And yet, when we think about it – Nature provides several services that we take for granted… until they aren’t there anymore. Clean air for example – natural systems have filtered and purified air around cities and homes for many years, until the output from our cities becomes too much for the natural system and then we start noticing the smog and pollution. Or flood control – mangroves in the coastal areas of the tropics provide buffers against storm surges and flooding from hurricanes, until they are cut down for development and then we are faced with multi-million dollar damages from a storm.   Several ecologists and economists have worked together to try and figure out how best to quantify or price the services that natural systems provide, often called ecosystem services. But what happens as the environment changes, the climate warms and several ecosystems are t

  Most of us working in the sustainability and clean tech space have heard of “ Smart Cities ” – one of the buzzwords in the clean tech and data science space since 2014. It’s usually used in the context of building better sensors or using artificial intelligence so that certain aspects of living in cities become automated, efficient and   sustainable.   These could be a number of things – better waste management, more efficient lighting, energy efficient buildings across the city, increased green spaces, less water use and so on and so on… As more of the world’s population starts living in cities, it’s critical that we make our cities as livable and sustainable as possible. And that means using all the latest tools at our disposal, especially the new methods by which data are collected and stored in the cloud today. One of the most fascinating aspects of working in the data science space has been the explosion in data that are freely available or available at a relatively low cost as